{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入包\n",
    "import pandas as pd\n",
    "import torch\n",
    "from torch import nn\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from torch.utils.data import DataLoader,Dataset, TensorDataset\n",
    "\n",
    "# 读取数据\n",
    "data = pd.read_csv('suning.csv', encoding = 'gbk')\n",
    "# 删除空值的行\n",
    "data = data.drop(data[data['涨跌额'].str.contains('None')].index)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 把数据设置成统一的float数据类型\n",
    "data[\"涨跌额\"] = data['涨跌额'].astype(\"float\")\n",
    "data[\"最高价\"] = data['最高价'].astype(\"float\")\n",
    "data[\"最高价\"] = data['最高价'].astype(\"float\")\n",
    "data[\"开盘价\"] = data['开盘价'].astype(\"float\")\n",
    "data[\"涨跌幅\"] = data['涨跌幅'].astype(\"float\")\n",
    "data[\"换手率\"] = data['换手率'].astype(\"float\")\n",
    "\n",
    "\n",
    "# 导入数据和预测值\n",
    "datas = data[data.columns[4:7]].values\n",
    "labels = data[data.columns[3]].values\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LSTM(\n",
      "  (lstm): LSTM(1, 2, num_layers=2)\n",
      "  (linear): Linear(in_features=3, out_features=10, bias=True)\n",
      "  (linear1): Linear(in_features=10, out_features=8, bias=True)\n",
      "  (linear3): Linear(in_features=8, out_features=2, bias=True)\n",
      "  (linear4): Linear(in_features=2, out_features=1, bias=True)\n",
      ")\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda\\lib\\site-packages\\torch\\nn\\modules\\loss.py:432: UserWarning: Using a target size (torch.Size([692])) that is different to the input size (torch.Size([692, 1])). This will likely lead to incorrect results due to broadcasting. Please ensure they have the same size.\n",
      "  return F.mse_loss(input, target, reduction=self.reduction)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1abf0a3fd48>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = TensorDataset(torch.tensor(np.array(datas.reshape(-1, 3))[3000:]), torch.tensor(np.array(labels))[3000:])\n",
    "dataloader = DataLoader(dataset, batch_size=len(dataset),shuffle=True, drop_last=False)\n",
    "\n",
    "class LSTM(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(LSTM, self).__init__()\n",
    "    \n",
    "    \n",
    "        self.lstm = nn.LSTM(1, 2,2)\n",
    "        self.linear = nn.Linear(3, 10)\n",
    "        self.linear1 = nn.Linear(10,8)\n",
    "        self.linear3 = nn.Linear(8,2)\n",
    "        self.linear4 = nn.Linear(2,1)\n",
    "\n",
    "    \n",
    "    def forward(self,x):\n",
    "        x1 = x.clone()\n",
    "        x1,_ = self.lstm(x1.reshape(-1 ,3,1))\n",
    "        a,b,c = x1.shape\n",
    "        out = self.linear4(x1.view(-1,c))\n",
    "        out1 = out.view(a,b,-1)\n",
    "        out = self.linear(x)\n",
    "        out = self.linear1(out)\n",
    "        out = self.linear3(out)\n",
    "        out = self.linear4(out)\n",
    "\n",
    "        \n",
    "        \n",
    "        return out\n",
    "\n",
    "\n",
    "rnn = LSTM()\n",
    "print(rnn)\n",
    "\n",
    "optimizer = torch.optim.Adam(rnn.parameters(), lr=0.02)   # optimize all cnn parameters\n",
    "loss_func = nn.MSELoss()\n",
    "\n",
    "#h_state = None      # for initial hidden state\n",
    "\n",
    "\n",
    "for epoch in range(20):\n",
    "    for step,(b_x, b_y) in enumerate(dataloader):\n",
    "\n",
    "\n",
    "        prediction = rnn(b_x.float())   # rnn output\n",
    "        # !! next step is important !!\n",
    "        #h_state = h_state.data        # repack the hidden state, break the connection from last iteration\n",
    "\n",
    "        #print(prediction, b_y.float())\n",
    "        loss = loss_func(prediction, b_y.float())         # calculate loss\n",
    "        #print(loss.data.numpy())\n",
    "        optimizer.zero_grad()                   # clear gradients for this training step\n",
    "        loss.backward()                         # backpropagation, compute gradients\n",
    "        optimizer.step()                        # apply gradients\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(rnn(b_x.float()).view(-1).data.numpy()[:50])\n",
    "plt.plot(b_y[:50].data.numpy())\n",
    "plt.title('Predict')\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('price')\n",
    "plt.savefig('lstm.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
